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What Lays Ahead in 2024? AI/ML Predictions for the New Year

Iguazio

2023 was the year of generative AI, with applications like ChatGPT, Bard and others becoming so mainstream we almost forgot what it was like to live in a world without them. This means that in 2024, we’re likely to see businesses continue to seek ways to adopt generative AI as a way to enhance their operations.

ML 64
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What Lays Ahead in 2024? AI/ML Predictions for the New Year

Iguazio

2023 was the year of generative AI, with applications like ChatGPT, Bard and others becoming so mainstream we almost forgot what it was like to live in a world without them. This means that in 2024, we’re likely to see businesses continue to seek ways to adopt generative AI as a way to enhance their operations.

ML 52
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ML Collaboration: Best Practices From 4 ML Teams

The MLOps Blog

As per a report by McKinsey , AI has the potential to contribute USD 13 trillion to the global economy by 2030. The onset of the pandemic has triggered a rapid increase in the demand and adoption of ML technology. A large part of building successful ML teams depends on the size of the organization and its strategic vision.

ML 78
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How to Build an End-To-End ML Pipeline

The MLOps Blog

One of the most prevalent complaints we hear from ML engineers in the community is how costly and error-prone it is to manually go through the ML workflow of building and deploying models. Building end-to-end machine learning pipelines lets ML engineers build once, rerun, and reuse many times.

ML 98
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Implementing Gen AI for Financial Services

Iguazio

Gen AI is quickly reshaping industries, and the pace of innovation is incredible to witness. While building gen AI application pilots is fairly straightforward, scaling them to production-ready, customer-facing implementations is a novel challenge for enterprises, and especially for the financial services sector.

AI 52
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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

Alignment to other tools in the organization’s tech stack Consider how well the MLOps tool integrates with your existing tools and workflows, such as data sources, data engineering platforms, code repositories, CI/CD pipelines, monitoring systems, etc. and Pandas or Apache Spark DataFrames.

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Future-Proofing Your App: Strategies for Building Long-Lasting Apps

Iguazio

The generative AI industry is changing fast. New models and technologies (Hello GPT-4o) are emerging regularly, each more advanced than the last. They also need to understand regulatory and ethical implications of deploying AI models, taking into consideration issues like data privacy, security and ethical AI use.